Overview

Dataset statistics

Number of variables10
Number of observations999
Missing cells387
Missing cells (%)3.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory760.4 KiB
Average record size in memory779.5 B

Variable types

Text3
DateTime1
Categorical1
Numeric5

Alerts

complexity has 387 (38.7%) missing valuesMissing
views is highly skewed (γ1 = 27.97413589)Skewed
published_datetime has unique valuesUnique
title has unique valuesUnique
votes has 50 (5.0%) zerosZeros
comments has 109 (10.9%) zerosZeros

Reproduction

Analysis started2024-03-16 11:24:58.699449
Analysis finished2024-03-16 11:25:01.755497
Duration3.06 seconds
Software versionydata-profiling vv4.6.5
Download configurationconfig.json

Variables

author
Text

Distinct571
Distinct (%)57.2%
Missing0
Missing (%)0.0%
Memory size64.6 KiB
2024-03-16T14:25:01.854234image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length23
Median length19
Mean length9.0930931
Min length3

Characters and Unicode

Total characters9084
Distinct characters64
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique427 ?
Unique (%)42.7%

Sample

1st rowits_capitan
2nd rowyadro_team
3rd rowTaritsyn
4th rowpomazkovjs
5th rowsergeytolkachyov
ValueCountFrequency (%)
aio350 51
 
5.1%
gmtd 18
 
1.8%
sergeytolkachyov 14
 
1.4%
mr-pickles 14
 
1.4%
melnik909 13
 
1.3%
simbirsoft_frontend 11
 
1.1%
rostislavdugin 10
 
1.0%
qmzik 10
 
1.0%
nin-jin 10
 
1.0%
parker0 10
 
1.0%
Other values (561) 838
83.9%
2024-03-16T14:25:02.153465image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 829
 
9.1%
o 664
 
7.3%
i 633
 
7.0%
e 629
 
6.9%
r 527
 
5.8%
n 511
 
5.6%
s 400
 
4.4%
t 397
 
4.4%
l 369
 
4.1%
k 339
 
3.7%
Other values (54) 3786
41.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 7619
83.9%
Uppercase Letter 823
 
9.1%
Decimal Number 441
 
4.9%
Connector Punctuation 153
 
1.7%
Dash Punctuation 48
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 829
 
10.9%
o 664
 
8.7%
i 633
 
8.3%
e 629
 
8.3%
r 527
 
6.9%
n 511
 
6.7%
s 400
 
5.3%
t 397
 
5.2%
l 369
 
4.8%
k 339
 
4.4%
Other values (16) 2321
30.5%
Uppercase Letter
ValueCountFrequency (%)
S 96
 
11.7%
M 60
 
7.3%
B 59
 
7.2%
A 57
 
6.9%
D 54
 
6.6%
G 49
 
6.0%
P 48
 
5.8%
L 48
 
5.8%
T 42
 
5.1%
R 37
 
4.5%
Other values (16) 273
33.2%
Decimal Number
ValueCountFrequency (%)
0 105
23.8%
3 76
17.2%
5 68
15.4%
1 53
12.0%
9 38
 
8.6%
2 34
 
7.7%
4 19
 
4.3%
7 18
 
4.1%
6 16
 
3.6%
8 14
 
3.2%
Connector Punctuation
ValueCountFrequency (%)
_ 153
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 8442
92.9%
Common 642
 
7.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 829
 
9.8%
o 664
 
7.9%
i 633
 
7.5%
e 629
 
7.5%
r 527
 
6.2%
n 511
 
6.1%
s 400
 
4.7%
t 397
 
4.7%
l 369
 
4.4%
k 339
 
4.0%
Other values (42) 3144
37.2%
Common
ValueCountFrequency (%)
_ 153
23.8%
0 105
16.4%
3 76
11.8%
5 68
10.6%
1 53
 
8.3%
- 48
 
7.5%
9 38
 
5.9%
2 34
 
5.3%
4 19
 
3.0%
7 18
 
2.8%
Other values (2) 30
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9084
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 829
 
9.1%
o 664
 
7.3%
i 633
 
7.0%
e 629
 
6.9%
r 527
 
5.8%
n 511
 
5.6%
s 400
 
4.4%
t 397
 
4.4%
l 369
 
4.1%
k 339
 
3.7%
Other values (54) 3786
41.7%

published_datetime
Date

UNIQUE 

Distinct999
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
Minimum2022-08-31 08:17:44+00:00
Maximum2024-03-16 06:38:28+00:00
2024-03-16T14:25:02.297081image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-16T14:25:02.437673image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

title
Text

UNIQUE 

Distinct999
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size280.2 KiB
2024-03-16T14:25:02.598276image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length120
Median length89
Mean length55.664665
Min length10

Characters and Unicode

Total characters55609
Distinct characters166
Distinct categories14 ?
Distinct scripts3 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique999 ?
Unique (%)100.0%

Sample

1st row$2500 в месяц на сервисе с 1 функцией, которая уже была у крупных компаний
2nd row«Код-ревью — это когда твои комментарии в интернете действительно читают»: дискуссия с разработчиками на C++
3rd rowВысказывания трех известных людей о проблемах современной разработки ПО
4th rowПолное краткое руководство по grammY — JS-библиотеке для создания Telegram-ботов
5th rowДобавление своих команд для CLI в Joomla 4 и Joomla 5 с помощью плагина
ValueCountFrequency (%)
в 299
 
3.7%
и 274
 
3.4%
как 215
 
2.7%
с 171
 
2.1%
на 168
 
2.1%
для 128
 
1.6%
81
 
1.0%
часть 59
 
0.7%
react 55
 
0.7%
не 54
 
0.7%
Other values (3495) 6582
81.4%
2024-03-16T14:25:02.911438image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7068
 
12.7%
о 3594
 
6.5%
а 3364
 
6.0%
и 3130
 
5.6%
е 3057
 
5.5%
т 2459
 
4.4%
н 2271
 
4.1%
р 2184
 
3.9%
с 1828
 
3.3%
в 1547
 
2.8%
Other values (156) 25107
45.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 43186
77.7%
Space Separator 7089
 
12.7%
Uppercase Letter 3388
 
6.1%
Other Punctuation 839
 
1.5%
Decimal Number 536
 
1.0%
Dash Punctuation 352
 
0.6%
Math Symbol 59
 
0.1%
Close Punctuation 43
 
0.1%
Open Punctuation 43
 
0.1%
Final Punctuation 33
 
0.1%
Other values (4) 41
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
о 3594
 
8.3%
а 3364
 
7.8%
и 3130
 
7.2%
е 3057
 
7.1%
т 2459
 
5.7%
н 2271
 
5.3%
р 2184
 
5.1%
с 1828
 
4.2%
в 1547
 
3.6%
к 1501
 
3.5%
Other values (56) 18251
42.3%
Uppercase Letter
ValueCountFrequency (%)
S 390
 
11.5%
К 208
 
6.1%
P 184
 
5.4%
C 166
 
4.9%
T 162
 
4.8%
R 136
 
4.0%
A 136
 
4.0%
П 114
 
3.4%
С 101
 
3.0%
M 98
 
2.9%
Other values (42) 1693
50.0%
Other Punctuation
ValueCountFrequency (%)
. 251
29.9%
, 237
28.2%
: 218
26.0%
? 75
 
8.9%
/ 21
 
2.5%
8
 
1.0%
! 7
 
0.8%
& 6
 
0.7%
% 5
 
0.6%
# 3
 
0.4%
Other values (5) 8
 
1.0%
Decimal Number
ValueCountFrequency (%)
2 142
26.5%
0 115
21.5%
1 91
17.0%
3 69
12.9%
4 38
 
7.1%
5 26
 
4.9%
6 17
 
3.2%
7 16
 
3.0%
8 15
 
2.8%
9 7
 
1.3%
Math Symbol
ValueCountFrequency (%)
+ 44
74.6%
= 5
 
8.5%
| 3
 
5.1%
2
 
3.4%
> 2
 
3.4%
< 2
 
3.4%
~ 1
 
1.7%
Space Separator
ValueCountFrequency (%)
7068
99.7%
  19
 
0.3%
2
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 265
75.3%
81
 
23.0%
6
 
1.7%
Close Punctuation
ValueCountFrequency (%)
) 41
95.3%
] 2
 
4.7%
Open Punctuation
ValueCountFrequency (%)
( 41
95.3%
[ 2
 
4.7%
Final Punctuation
ValueCountFrequency (%)
» 31
93.9%
2
 
6.1%
Initial Punctuation
ValueCountFrequency (%)
« 31
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 5
100.0%
Other Symbol
ValueCountFrequency (%)
3
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Cyrillic 38120
68.6%
Common 9042
 
16.3%
Latin 8447
 
15.2%

Most frequent character per script

Cyrillic
ValueCountFrequency (%)
о 3594
 
9.4%
а 3364
 
8.8%
и 3130
 
8.2%
е 3057
 
8.0%
т 2459
 
6.5%
н 2271
 
6.0%
р 2184
 
5.7%
с 1828
 
4.8%
в 1547
 
4.1%
к 1501
 
3.9%
Other values (49) 13185
34.6%
Common
ValueCountFrequency (%)
7068
78.2%
- 265
 
2.9%
. 251
 
2.8%
, 237
 
2.6%
: 218
 
2.4%
2 142
 
1.6%
0 115
 
1.3%
1 91
 
1.0%
81
 
0.9%
? 75
 
0.8%
Other values (45) 499
 
5.5%
Latin
ValueCountFrequency (%)
e 812
 
9.6%
a 568
 
6.7%
t 540
 
6.4%
o 472
 
5.6%
r 450
 
5.3%
S 390
 
4.6%
i 389
 
4.6%
n 346
 
4.1%
s 311
 
3.7%
c 310
 
3.7%
Other values (42) 3859
45.7%

Most occurring blocks

ValueCountFrequency (%)
Cyrillic 38120
68.6%
ASCII 17295
31.1%
Punctuation 99
 
0.2%
None 83
 
0.1%
Math Alphanum 7
 
< 0.1%
Letterlike Symbols 3
 
< 0.1%
Arrows 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7068
40.9%
e 812
 
4.7%
a 568
 
3.3%
t 540
 
3.1%
o 472
 
2.7%
r 450
 
2.6%
S 390
 
2.3%
i 389
 
2.2%
n 346
 
2.0%
s 311
 
1.8%
Other values (79) 5949
34.4%
Cyrillic
ValueCountFrequency (%)
о 3594
 
9.4%
а 3364
 
8.8%
и 3130
 
8.2%
е 3057
 
8.0%
т 2459
 
6.5%
н 2271
 
6.0%
р 2184
 
5.7%
с 1828
 
4.8%
в 1547
 
4.1%
к 1501
 
3.9%
Other values (49) 13185
34.6%
Punctuation
ValueCountFrequency (%)
81
81.8%
8
 
8.1%
6
 
6.1%
2
 
2.0%
2
 
2.0%
None
ValueCountFrequency (%)
» 31
37.3%
« 31
37.3%
  19
22.9%
2
 
2.4%
Letterlike Symbols
ValueCountFrequency (%)
3
100.0%
Arrows
ValueCountFrequency (%)
2
100.0%
Math Alphanum
ValueCountFrequency (%)
𝚍 1
14.3%
𝚒 1
14.3%
𝚛 1
14.3%
𝚊 1
14.3%
𝚞 1
14.3%
𝚝 1
14.3%
𝚘 1
14.3%

complexity
Categorical

MISSING 

Distinct3
Distinct (%)0.5%
Missing387
Missing (%)38.7%
Memory size90.7 KiB
Простой
297 
Средний
291 
Сложный
 
24

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters4284
Distinct characters14
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowПростой
2nd rowПростой
3rd rowПростой
4th rowПростой
5th rowСредний

Common Values

ValueCountFrequency (%)
Простой 297
29.7%
Средний 291
29.1%
Сложный 24
 
2.4%
(Missing) 387
38.7%

Length

2024-03-16T14:25:03.035076image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T14:25:03.122841image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
простой 297
48.5%
средний 291
47.5%
сложный 24
 
3.9%

Most occurring characters

ValueCountFrequency (%)
о 618
14.4%
й 612
14.3%
р 588
13.7%
С 315
7.4%
н 315
7.4%
П 297
6.9%
с 297
6.9%
т 297
6.9%
е 291
6.8%
д 291
6.8%
Other values (4) 363
8.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3672
85.7%
Uppercase Letter 612
 
14.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
о 618
16.8%
й 612
16.7%
р 588
16.0%
н 315
8.6%
с 297
8.1%
т 297
8.1%
е 291
7.9%
д 291
7.9%
и 291
7.9%
л 24
 
0.7%
Other values (2) 48
 
1.3%
Uppercase Letter
ValueCountFrequency (%)
С 315
51.5%
П 297
48.5%

Most occurring scripts

ValueCountFrequency (%)
Cyrillic 4284
100.0%

Most frequent character per script

Cyrillic
ValueCountFrequency (%)
о 618
14.4%
й 612
14.3%
р 588
13.7%
С 315
7.4%
н 315
7.4%
П 297
6.9%
с 297
6.9%
т 297
6.9%
е 291
6.8%
д 291
6.8%
Other values (4) 363
8.5%

Most occurring blocks

ValueCountFrequency (%)
Cyrillic 4284
100.0%

Most frequent character per block

Cyrillic
ValueCountFrequency (%)
о 618
14.4%
й 612
14.3%
р 588
13.7%
С 315
7.4%
н 315
7.4%
П 297
6.9%
с 297
6.9%
т 297
6.9%
е 291
6.8%
д 291
6.8%
Other values (4) 363
8.5%

reading_time
Real number (ℝ)

Distinct38
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.4094094
Minimum1
Maximum62
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2024-03-16T14:25:03.222605image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q15
median7
Q310
95-th percentile19.1
Maximum62
Range61
Interquartile range (IQR)5

Descriptive statistics

Standard deviation6.1306379
Coefficient of variation (CV)0.72902122
Kurtosis11.445441
Mean8.4094094
Median Absolute Deviation (MAD)3
Skewness2.6270229
Sum8401
Variance37.584721
MonotonicityNot monotonic
2024-03-16T14:25:03.338264image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
5 130
13.0%
4 114
11.4%
6 102
10.2%
7 97
9.7%
8 89
8.9%
3 87
8.7%
10 52
 
5.2%
9 49
 
4.9%
2 35
 
3.5%
12 34
 
3.4%
Other values (28) 210
21.0%
ValueCountFrequency (%)
1 6
 
0.6%
2 35
 
3.5%
3 87
8.7%
4 114
11.4%
5 130
13.0%
6 102
10.2%
7 97
9.7%
8 89
8.9%
9 49
 
4.9%
10 52
 
5.2%
ValueCountFrequency (%)
62 1
 
0.1%
50 1
 
0.1%
40 1
 
0.1%
37 1
 
0.1%
34 4
0.4%
33 4
0.4%
32 2
0.2%
31 2
0.2%
30 1
 
0.1%
29 3
0.3%

views
Real number (ℝ)

SKEWED 

Distinct165
Distinct (%)16.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11447.273
Minimum241
Maximum1500000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2024-03-16T14:25:03.458974image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum241
5-th percentile1300
Q13250
median6000
Q312000
95-th percentile31000
Maximum1500000
Range1499759
Interquartile range (IQR)8750

Descriptive statistics

Standard deviation49187.977
Coefficient of variation (CV)4.2969165
Kurtosis842.95181
Mean11447.273
Median Absolute Deviation (MAD)3300
Skewness27.974136
Sum11435826
Variance2.4194571 × 109
MonotonicityNot monotonic
2024-03-16T14:25:03.593581image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13000 30
 
3.0%
11000 29
 
2.9%
12000 26
 
2.6%
15000 20
 
2.0%
14000 17
 
1.7%
3100 16
 
1.6%
2800 15
 
1.5%
2300 15
 
1.5%
4600 15
 
1.5%
3800 15
 
1.5%
Other values (155) 801
80.2%
ValueCountFrequency (%)
241 1
0.1%
370 1
0.1%
534 1
0.1%
642 1
0.1%
652 1
0.1%
694 1
0.1%
751 1
0.1%
776 1
0.1%
804 1
0.1%
805 1
0.1%
ValueCountFrequency (%)
1500000 1
0.1%
209000 1
0.1%
189000 1
0.1%
116000 1
0.1%
84000 1
0.1%
78000 1
0.1%
76000 1
0.1%
73000 1
0.1%
71000 2
0.2%
69000 1
0.1%

tags
Text

Distinct752
Distinct (%)75.3%
Missing0
Missing (%)0.0%
Memory size290.6 KiB
2024-03-16T14:25:03.789868image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length127
Median length92
Mean length58.401401
Min length14

Characters and Unicode

Total characters58343
Distinct characters124
Distinct categories13 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique653 ?
Unique (%)65.4%

Sample

1st rowВеб-разработка Монетизация веб-сервисов Развитие стартапа Управление продуктом Бизнес-модели
2nd rowБлог компании YADRO Веб-разработка C++ Конференции IT-компании
3rd rowВеб-разработка Управление разработкой Управление персоналом История IT
4th rowБлог компании Selectel Веб-разработка Программирование
5th rowВеб-разработка Open source PHP Joomla
ValueCountFrequency (%)
веб-разработка 999
 
16.5%
блог 418
 
6.9%
компании 418
 
6.9%
javascript 301
 
5.0%
программирование 200
 
3.3%
reactjs 122
 
2.0%
typescript 104
 
1.7%
html 92
 
1.5%
и 88
 
1.5%
разработка 88
 
1.5%
Other values (391) 3214
53.2%
2024-03-16T14:25:04.431121image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
а 5413
 
9.3%
5045
 
8.6%
р 3878
 
6.6%
о 3696
 
6.3%
и 3100
 
5.3%
е 2816
 
4.8%
б 2414
 
4.1%
т 2049
 
3.5%
н 2040
 
3.5%
к 2040
 
3.5%
Other values (114) 25852
44.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 44875
76.9%
Uppercase Letter 6990
 
12.0%
Space Separator 5045
 
8.6%
Dash Punctuation 1223
 
2.1%
Other Punctuation 117
 
0.2%
Decimal Number 20
 
< 0.1%
Open Punctuation 17
 
< 0.1%
Close Punctuation 17
 
< 0.1%
Final Punctuation 11
 
< 0.1%
Initial Punctuation 11
 
< 0.1%
Other values (3) 17
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
а 5413
 
12.1%
р 3878
 
8.6%
о 3696
 
8.2%
и 3100
 
6.9%
е 2816
 
6.3%
б 2414
 
5.4%
т 2049
 
4.6%
н 2040
 
4.5%
к 2040
 
4.5%
з 1458
 
3.2%
Other values (46) 15971
35.6%
Uppercase Letter
ValueCountFrequency (%)
В 1101
15.8%
S 1011
14.5%
J 543
 
7.8%
Б 475
 
6.8%
T 419
 
6.0%
П 270
 
3.9%
P 270
 
3.9%
C 200
 
2.9%
R 191
 
2.7%
I 188
 
2.7%
Other values (39) 2322
33.2%
Other Punctuation
ValueCountFrequency (%)
. 106
90.6%
# 7
 
6.0%
* 2
 
1.7%
/ 1
 
0.9%
& 1
 
0.9%
Decimal Number
ValueCountFrequency (%)
1 8
40.0%
3 5
25.0%
8 3
 
15.0%
5 2
 
10.0%
2 2
 
10.0%
Space Separator
ValueCountFrequency (%)
5045
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1223
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Final Punctuation
ValueCountFrequency (%)
» 11
100.0%
Initial Punctuation
ValueCountFrequency (%)
« 11
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 8
100.0%
Math Symbol
ValueCountFrequency (%)
+ 6
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Cyrillic 39492
67.7%
Latin 12373
 
21.2%
Common 6478
 
11.1%

Most frequent character per script

Cyrillic
ValueCountFrequency (%)
а 5413
13.7%
р 3878
 
9.8%
о 3696
 
9.4%
и 3100
 
7.8%
е 2816
 
7.1%
б 2414
 
6.1%
т 2049
 
5.2%
н 2040
 
5.2%
к 2040
 
5.2%
з 1458
 
3.7%
Other values (45) 10588
26.8%
Latin
ValueCountFrequency (%)
S 1011
 
8.2%
a 953
 
7.7%
e 872
 
7.0%
t 761
 
6.2%
c 737
 
6.0%
r 675
 
5.5%
i 666
 
5.4%
p 591
 
4.8%
J 543
 
4.4%
o 483
 
3.9%
Other values (40) 5081
41.1%
Common
ValueCountFrequency (%)
5045
77.9%
- 1223
 
18.9%
. 106
 
1.6%
( 17
 
0.3%
) 17
 
0.3%
» 11
 
0.2%
« 11
 
0.2%
1 8
 
0.1%
$ 8
 
0.1%
# 7
 
0.1%
Other values (9) 25
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Cyrillic 39492
67.7%
ASCII 18829
32.3%
None 22
 
< 0.1%

Most frequent character per block

Cyrillic
ValueCountFrequency (%)
а 5413
13.7%
р 3878
 
9.8%
о 3696
 
9.4%
и 3100
 
7.8%
е 2816
 
7.1%
б 2414
 
6.1%
т 2049
 
5.2%
н 2040
 
5.2%
к 2040
 
5.2%
з 1458
 
3.7%
Other values (45) 10588
26.8%
ASCII
ValueCountFrequency (%)
5045
26.8%
- 1223
 
6.5%
S 1011
 
5.4%
a 953
 
5.1%
e 872
 
4.6%
t 761
 
4.0%
c 737
 
3.9%
r 675
 
3.6%
i 666
 
3.5%
p 591
 
3.1%
Other values (57) 6295
33.4%
None
ValueCountFrequency (%)
» 11
50.0%
« 11
50.0%

votes
Real number (ℝ)

ZEROS 

Distinct96
Distinct (%)9.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.302302
Minimum0
Maximum271
Zeros50
Zeros (%)5.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2024-03-16T14:25:04.574769image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.9
Q14
median8
Q317.5
95-th percentile57.2
Maximum271
Range271
Interquartile range (IQR)13.5

Descriptive statistics

Standard deviation25.042983
Coefficient of variation (CV)1.5361624
Kurtosis23.254881
Mean16.302302
Median Absolute Deviation (MAD)6
Skewness4.0880164
Sum16286
Variance627.15101
MonotonicityNot monotonic
2024-03-16T14:25:04.707940image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3 77
 
7.7%
2 70
 
7.0%
4 68
 
6.8%
5 55
 
5.5%
1 51
 
5.1%
6 51
 
5.1%
0 50
 
5.0%
7 43
 
4.3%
8 40
 
4.0%
10 34
 
3.4%
Other values (86) 460
46.0%
ValueCountFrequency (%)
0 50
5.0%
1 51
5.1%
2 70
7.0%
3 77
7.7%
4 68
6.8%
5 55
5.5%
6 51
5.1%
7 43
4.3%
8 40
4.0%
9 34
3.4%
ValueCountFrequency (%)
271 1
0.1%
190 1
0.1%
177 1
0.1%
171 1
0.1%
167 1
0.1%
166 1
0.1%
152 1
0.1%
148 1
0.1%
144 1
0.1%
142 1
0.1%

bookmarks
Real number (ℝ)

Distinct187
Distinct (%)18.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean57.103103
Minimum2
Maximum748
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2024-03-16T14:25:04.835205image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile8
Q121
median38
Q371
95-th percentile171.1
Maximum748
Range746
Interquartile range (IQR)50

Descriptive statistics

Standard deviation60.856647
Coefficient of variation (CV)1.0657327
Kurtosis32.347019
Mean57.103103
Median Absolute Deviation (MAD)22
Skewness4.1645549
Sum57046
Variance3703.5314
MonotonicityNot monotonic
2024-03-16T14:25:04.966853image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15 22
 
2.2%
19 21
 
2.1%
29 21
 
2.1%
26 21
 
2.1%
31 20
 
2.0%
27 19
 
1.9%
9 18
 
1.8%
30 16
 
1.6%
8 16
 
1.6%
20 16
 
1.6%
Other values (177) 809
81.0%
ValueCountFrequency (%)
2 2
 
0.2%
3 7
 
0.7%
5 8
0.8%
6 12
1.2%
7 11
1.1%
8 16
1.6%
9 18
1.8%
10 15
1.5%
11 12
1.2%
12 14
1.4%
ValueCountFrequency (%)
748 1
0.1%
655 1
0.1%
586 1
0.1%
300 1
0.1%
296 1
0.1%
282 1
0.1%
281 1
0.1%
274 1
0.1%
273 1
0.1%
266 1
0.1%

comments
Real number (ℝ)

ZEROS 

Distinct108
Distinct (%)10.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.121121
Minimum0
Maximum596
Zeros109
Zeros (%)10.9%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2024-03-16T14:25:05.098501image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median7
Q316
95-th percentile79
Maximum596
Range596
Interquartile range (IQR)13

Descriptive statistics

Standard deviation45.854592
Coefficient of variation (CV)2.3981121
Kurtosis55.859056
Mean19.121121
Median Absolute Deviation (MAD)5
Skewness6.5635358
Sum19102
Variance2102.6436
MonotonicityNot monotonic
2024-03-16T14:25:05.231159image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 109
 
10.9%
2 78
 
7.8%
4 72
 
7.2%
3 68
 
6.8%
5 59
 
5.9%
1 57
 
5.7%
6 46
 
4.6%
7 39
 
3.9%
9 38
 
3.8%
10 33
 
3.3%
Other values (98) 400
40.0%
ValueCountFrequency (%)
0 109
10.9%
1 57
5.7%
2 78
7.8%
3 68
6.8%
4 72
7.2%
5 59
5.9%
6 46
4.6%
7 39
 
3.9%
8 28
 
2.8%
9 38
 
3.8%
ValueCountFrequency (%)
596 1
0.1%
457 1
0.1%
445 1
0.1%
414 1
0.1%
346 1
0.1%
327 1
0.1%
308 1
0.1%
302 1
0.1%
274 1
0.1%
268 1
0.1%

Interactions

2024-03-16T14:25:01.033354image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-16T14:24:59.006774image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-16T14:24:59.482502image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-16T14:25:00.010092image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-16T14:25:00.533691image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-16T14:25:01.126181image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-16T14:24:59.097532image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-16T14:24:59.577249image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-16T14:25:00.099850image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-16T14:25:00.647387image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-16T14:25:01.226912image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-16T14:24:59.193275image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-16T14:24:59.683964image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-16T14:25:00.196592image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-16T14:25:00.747120image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-16T14:25:01.317668image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-16T14:24:59.292011image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-16T14:24:59.790679image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-16T14:25:00.283360image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-16T14:25:00.840880image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-16T14:25:01.414409image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-16T14:24:59.389750image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-16T14:24:59.907370image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-16T14:25:00.401049image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-16T14:25:00.936613image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Missing values

2024-03-16T14:25:01.541106image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-16T14:25:01.689673image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

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